1 The statistics in this publication were compiled from data collected in the Survey of Education and Training (SET) which was conducted throughout Australia from March to June 2009.

2 The SET provides a range of key indicators on educational participation, attainment and learning. Detailed information on the following topics was collected:

General demographic information

Parental information

educational attainment

employment status

occupation

Employment characteristics

labour force status

occupation

industry

sector of employment

duration of employment or unemployment

hours worked

trade union membership

Participation in education

school

current study

educational attainment

formal learning in the last 12 months

Education and employment outcomes

first qualification

most recent qualification

Non-formal learning

work-related courses

types of financial support

types of expenses

participation in training

time spent on training

training costs

Informal learning

Barriers to learning

access

difficulties

Health and disability

Personal income

3 The statistics included in this publication present a broad overview of the data items collected in the SET. Emphasis has been given to providing information on key measures such as educational attainment and participation in education and training.

SCOPE OF THE SURVEY

4 The SET is a household survey which was conducted in both urban and rural areas in all states and territories, except for very remote parts of Australia. Queensland, South Australia, Western Australia and the Northern Territory all have very remote areas. With the exception of the Northern Territory, the population living in very remote areas represents only a small proportion of the total population (approximately 2%). For this, and other practical reasons, no adjustment was made to state population benchmarks when deriving the survey results. This exclusion is unlikely to impact on national estimates, and will only have a minor impact on any aggregate estimates that are produced for individual states and territories, except the Northern Territory where the excluded population accounts for over 23% of persons.

5 Only people who were usual residents of private dwellings in Australia were covered by the SET. Private dwellings are houses, flats, home units and any other structures used as private places of residence at the time of the survey. People usually resident in non-private dwellings such as hotels, motels, hostels, hospitals and short-stay caravan parks were not included in the survey. Usual residents are those persons who usually live in a particular dwelling and regard it as their own or main home. Visitors to private dwellings are not included in the interview for that dwelling. However, if they are a usual resident of another dwelling that is in the scope of the survey they have a chance of being selected in the survey or, if not selected, they will be represented by similar persons who are selected in the survey.

6 Persons aged 15-74 years were included in the scope of the SET. The bulk of the questionnaire was asked of persons in the population of interest which is those aged 15-64 years and persons aged 65-74 years who were in or marginally attached to the labour force. Persons aged 65-74 years who were in scope but not in the population of interest were sequenced to the end of the questionnaire once their labour force status had been established.

7 The following non-residents were excluded from the resident population estimates used to benchmark the SET results, and were not interviewed:

diplomatic personnel of overseas governments;

persons whose usual place of residence was outside Australia;

members of non-Australian defence forces (and their dependants) stationed in Australia.

SURVEY DESIGN

Sample size and selection

8 The 2009 SET was designed to provide reliable estimates at the national level and for each state and territory.

9 Dwellings in each state and territory were selected at random using a multi-stage area sample of private dwellings. The initial sample for the 2009 SET consisted of approximately 16,400 private dwellings. Of the approximately 13,200 households that remained in the survey after sample loss, approximately 11,800 (89%) were fully responding. As well as persons from fully responding households, SET included 452 fully responding persons from 292 partially responding households. The inclusion of these persons had an impact on the estimation of household income because of non-response by other members and this is further discussed in paragraph 31. In total, 23,807 persons fully responded to the 2009 SET.

SET FINAL SAMPLE, Number of persons - 2009

Capital City

Balance of State or Territory

Total

'000

'000

'000

New South Wales

2 271

1 460

3 731

Victoria

2 333

1 051

3 384

Queensland

1 372

1 577

2 949

South Australia

2 034

801

2 835

Western Australia

2 245

909

3 154

Tasmania

1 172

1 923

3 095

Northern Territory

1 371

406

1 777

Australian Capital Territory

2 882

-

2 882

Australia

15 680

8 127

23 807

- nil or rounded to zero (including null cells)

Non-responding households

10 Approximately 3,230 households in the 2009 SET did not respond at all to the questionnaire, or did not respond adequately. Such households included:

households affected by death or illness of a household member

households in which person(s) in the household did not respond because they could not be contacted, had language problems or refused to participate

households in which person(s) did not respond to key questions.

Partial response

11 Some households did not supply all the required information but supplied sufficient information to be retained in the SET sample. Such partial response occurred when:

at least one in scope person in the household responded but information could not be collected from the entire household. The information from the responding member(s) of the household was included however, some household details such as the estimation of household income are missing as information from all members of the household is incomplete.

earnings, income or training cost information is missing from a person's record because they are unable or unwilling to provide the data but they responded to other key variables in the survey.

DATA COLLECTION

12 Trained ABS interviewers conducted personal interviews at selected dwellings from the beginning of March 2009 to the end of June 2009. Interviews were conducted using a Computer Assisted Interviewing (CAI) questionnaire. CAI involves the use of a notebook computer to record, store, manipulate and transmit the data collected during interviews.

13 One person in the household, aged 18 years or over, provided basic household information including age, sex, Indigenous status, country of birth and relationships for all household members. Personal interviews were then conducted with all persons aged 15-74 years. The bulk of the questionnaire was asked of persons in the population of interest which is those aged 15-64 years and persons aged 65-74 years who were in or marginally attached to the labour force. Persons aged 65-74 years who were in scope but not in the population of interest were sequenced to the end of the questionnaire once their labour force status had been established.

WEIGHTING, BENCHMARKING AND ESTIMATION

Weighting

14 Weighting is the process of adjusting results from a sample survey to infer results for the total population. To do this, a 'weight' is allocated to each person. The weight is a value which indicates how many population units are represented by the sample unit.

15 The first step in calculating weights for each person is to assign an initial weight, which is equal to the inverse of the probability of being selected in the survey. For example, if the probability of a person being selected in the survey was 1 in 600, then the person would have an initial weight of 600 (that is, they represent 600 people).

Benchmarking

16 The SET weights were calibrated to align with independent estimates of the population by sex, age, state or territory of usual residence, section of state or territory and labour force status. Weights calibrated against population benchmarks ensure that the survey estimates conform to the independently estimated distribution of the population rather than to the distribution within the sample itself. Calibration to population benchmarks helps to compensate for over or under-enumeration of particular categories of persons which may occur due to either the random nature of sampling or non-response.

17 The 2009 SET was benchmarked to the estimated resident population (ERP) aged 15-74 years living in private dwellings in each state and territory, excluding the ERP living in very remote areas of Australia, at May 2009. The SET estimates do not (and are not intended to) match estimates for the total Australian resident population obtained from other sources (which include persons and households living in non-private dwellings such as hotels and boarding houses, and in very remote parts of Australia).

Estimation

18 Survey estimates of counts of persons are obtained by summing the weights of persons with the characteristic of interest. Estimates of other counts (i.e. training courses and qualifications) are obtained by multiplying the characteristic of interest by the weight of the reporting person, and then aggregating.

RELIABILITY OF ESTIMATES

19 All sample surveys are subject to error which can be broadly categorised as either:

sampling error; or

non-sampling error.

20 Sampling error occurs because only a small proportion of the total population is used to produce estimates that represent the whole population. Sampling error can be reliably measured as it is calculated based on the scientific methods used to design surveys.

21 Non-sampling error may occur at any stage throughout the survey process. For example, persons selected for the survey may not respond (non-response); survey questions may not be clearly understood by the respondent; responses may be incorrectly recorded by interviewers; or there may be errors in coding or processing survey data.

Sampling error

22 Sampling error is the difference between the published estimates, derived from a sample of persons, and the value that would have been produced if all persons in scope of the survey had been included. A measure of the sampling error for a given sample estimate is provided by the standard error, which may be expressed as a percentage of the estimate (relative standard error (RSE)). In this publication estimates with an RSE of 25% to 50% are preceded by an asterisk (e.g. *15.7) to indicate that the estimate should be used with caution. Estimates with RSEs over 50% are indicated by a double asterisk (e.g.**2.8) and should be considered unreliable for most purposes. For more information refer to the Technical Notes.

Non-sampling error

23 Non-sampling error may occur in any collection, whether it is based on a sample or a full count such as a census. One of the main sources of non-sampling error is non-response by persons selected in the survey. Non-response can affect the reliability of results and can introduce bias. The magnitude of any bias depends upon the level of non-response and the extent of the difference between the characteristics of those people who responded to the survey and those who did not.

24 Non-response occurs when persons cannot or will not cooperate, or cannot be contacted. Non-response can affect the reliability of results and can introduce a bias. The magnitude of any bias depends upon the rate of non-response and the extent of the difference between non-respondents' characteristics and those of persons who responded to the survey.

25 To reduce the level and impact of non-response the following methods were adopted in this survey:

face-to-face interviews with respondents;

the use of interviewers who could speak languages other than English where necessary;

follow-up of respondents if there was initially no response;

ensuring the weighted file is representative of the population by aligning the estimates with population benchmarks.

26 Every effort was made to reduce other non-sampling error by careful design and testing of the questionnaire, training and supervision of interviewers, and extensive editing and quality control procedures at all stages of data processing.

27 An advantage of the CAI technology used to conduct interviews for this survey is that it potentially reduces non-sampling errors by enabling edits to be applied as the data are being collected. The interviewer is alerted immediately if information entered into the computer is either outside the permitted range for that question, or contradictory to information previously recorded during the interview. These edits allow the interviewer to query respondents and resolve issues during the interview. CAI sequencing of questions is also automated so that respondents are only asked relevant questions and in the appropriate sequence, eliminating interviewer sequencing errors.

REFERENCE PERIOD AND SEASONAL EFFECTS

28 The estimates in this publication are based on information collected from March 2009 to June 2009 and, due to reference period and seasonal effects, they may not be fully representative of other time periods in the year. For example, the SET collected information on current study relating to persons enrolled in study at the time of their interview. As the period of collection for SET was from March to June, the reference period for data items on current study was four months. Estimates therefore include enrolments in the first half of 2009, as well as some enrolments which commenced in the second half of 2009. Enrolments are also subject to seasonal variation through the year. Therefore, the SET results could have differed if the survey had been conducted over the whole year or in a different part of the year.

INTERPRETATION OF RESULTS

29 Care has been taken to ensure that the results of this survey are as accurate as possible. All interviews were conducted by trained ABS officers. Extensive reference material was developed for use during field enumeration and intensive training was provided to interviewers. There remain, however, other factors which may have affected the reliability of results, and for which no specific adjustments can be made. The following factors should be considered when interpreting the 2009 SET estimates:

Information recorded in this survey is essentially 'as reported' by respondents, and hence may differ from information available from other sources or collected using different methodologies.

Responses may be affected by imperfect recall or individual interpretation of survey questions.

Some respondents may have provided responses that they felt were expected, rather than those that accurately reflected their own situation.

30 In addition, some respondents were unwilling or unable to provide the required information for a number of SET data items. Where responses for a particular data item were missing for a person or household they were recorded in a 'not known' or 'not stated' category for that data item. These 'not known' or 'not stated' categories are not explicitly shown in the publication tables, but have been included in the totals. Publication tables presenting proportions have included any 'not known' or 'not stated' categories in the calculation of these proportions.

31 For the personal gross weekly income data item, approximately 2000 people (8%) did not provide an income amount, either because they did not know their income or they refused to answer. Household income is the sum of the personal income of each person aged 15 years and over in the household. Where one person in the household either refused or did not know their income, the income for the household had to be classified as 'not known'. In some households, not all persons responded to the survey however, the records for those persons who did respond were included. Household income for these persons also had to be classified as 'not known'. Mean and median income excluded those households whose income was not known or inadequately reported. There were a number of other data items included in the publication that had missing values. The proportions of these missing values did not exceed 16% for any data item.

INCOME NON-REPONSE, Persons age 15-74

no.

%

Personal gross weekly income refused/not known

1 979.0

8.3

Total household gross weekly income not known due to personal income refused/not known

3 243.0

13.6

Total household gross weekly income not known due to partially responding household

452.0

1.9

Equivalised household gross weekly income not known

3 695.0

15.5

CLASSIFICATIONS

32 The 2009 SET used the following Australian standard classifications.

35 Field of Education is defined as the subject matter of an educational activity. Fields of education are related to each other through the similarity of subject matter, through the broad purpose for which the education is undertaken, and through the theoretical content which underpins the subject matter. There are 12 broad fields, 71 narrow fields and 356 detailed fields. For definitions of these fields see the Australian Standard Classification of Education, 2001 (cat. no. 1272.0).

37 The relationship between categories in the Level of Education classification should be essentially ordinal. In other words, educational activities at Broad Level 1 Postgraduate Degree should be at a higher level than those at Broad Level 2 Graduate Diploma and Graduate Certificate, and so on. However, when this idea is applied to the reality of educational provision in Australia, it is not always possible to assert that an ordinal relationship exists among the various levels of education.

38 This is particularly evident in the case of the relationship between Certificates I-IV in Broad Level 5 Certificate Level, and School Education included in Broad Level 6 Secondary Education. In this instance, the level of education associated with secondary education may range from satisfying the entry requirements for admission to a university degree course, to the completion of units in basic literacy, numeracy and life skills. Educational activity in these categories may therefore be of an equal, higher or lower level than Certificates found in Broad Level 5 Certificate Level.

39 Level of highest educational attainment was derived from information on highest year of school completed and level of highest non-school qualification. The derivation process determined which of the 'non-school' or 'school' attainments would be regarded as the highest. Usually the higher ranking attainment is self-evident, but in some cases some secondary education is regarded, for the purposes of obtaining a single measure, as higher than some certificate level attainments.

40 The following decision table was used to determine which of the responses to questions on highest year of school completed (coded to ASCED Broad Level 6) and level of highest non-school qualification (coded to ASCED Broad Level 5) was regarded as the highest. It is emphasised that this table was designed for the purpose of obtaining a single value for level of highest educational attainment and is not intended to convey any other ordinality.

41 The decision table was also used to rank the information provided in the SET about the qualifications and attainments of a single individual. It does not represent any basis for comparison between differing qualifications. For example, a person whose highest year of school completed was Year 12, and whose level of highest non-school qualification was a Certificate III, would have those responses crosschecked on the decision table and would as a result have their level of highest educational attainment output as Certificate III. However, if the same person answered 'certificate' to the highest non-school qualification question, without any further detail, it would be crosschecked against Year 12 on the decision table as Certificate not further defined. The output would then be Year 12. The decision table, therefore, does not necessarily imply that one qualification is 'higher' than the other. For more details, see Education Variables, 2002 (cat. no. 1246.0).

42 Level of education of current study was also derived using the decision table displayed above, taking into account Level of education of school study in current year and Level of education of non-school study in current year for persons who were undertaking concurrent qualifications.

45 All responses to language questions were coded to the Australian Standard Classification of Languages (ASCL), Second Edition, 2005-06 (cat. no. 1267.0). The 2009 SET questionnaire listed the 10 most frequently reported languages first spoken at home and the 10 most frequently reported main languages spoken at home on the basis of the statistical significance of these languages in the Australian context. Interviewers were instructed to mark the appropriate box, or if the reported language was not among those listed, to record the name of the language for subsequent coding.

48 Essentially the same methodology has been used since 1993 however the scope of the surveys has differed. While the scope of the 2009 survey included persons aged 15-74, the questions focused on persons aged 15-64 years and persons aged 65-74 years who were in or marginally attached to the labour force. The 2005 survey included all persons aged 15 years and over, with those aged 70 years and over asked a subset of questions, regardless of their employment status. The 2001 survey included all persons aged 15-64 years. In comparison, the scope of the 1997 survey was narrower and included persons aged 15-64 years who:

had worked as wage or salary earners in the previous 12 months;

were employed, unemployed or marginally attached to the labour force;

were aged 15-20 years and still at secondary school; and

were not in the labour force but were studying, or had studied in 1997.

49 The scope of the 1993 survey was even narrower than that of the 1997 survey. It included persons aged 15-64 years who had worked as wage or salary earners ('employees') in the last 12 months, as well as those who, at the time of the survey, were employers, self-employed, unemployed or marginally attached to the labour force, except:

persons aged 15-20 years still at school; and

persons working as unpaid family helpers or solely for payment in kind unless they had also held a wage or salary job in the last 12 months.

50 Other main differences between the surveys are as follows:

In 2009, 2005 and 2001, data were collected from Australian Defence Force Personnel living in private dwellings. However, this was not the case in 1997 or 1993.

For the 2009 and 2005 surveys, 'work-related training' only referred to courses undertaken to obtain, maintain or improve employment-related skills or competencies. For the 2001 survey, 'training' included 'on-the-job' training. In the 1997 survey the term 'training' also included any study undertaken towards the completion of an educational qualification. See the Glossary for more details.

51 There have also been a number of key questionnaire changes since the 2005 cycle which include:

the collection of detailed information about all qualifications completed (maximum 15) compared with only the three highest qualifications in 2005;

the introduction of an education and employment outcomes topic based on the 'First completed' and the 'Most recent completed' non-school qualification(s);

adopting the concepts of participation in formal, non-formal and informal learning undertaken in the last 12 months based on the international Classification of learning activities (CLA) which was developed by Eurostat and released in July 2006;

the collection of data about informal learning;

significant definitional changes to the 'work-related training' module which occurred as a result of a major review of SET, involving consultation with key stakeholders, which was undertaken during 2007. As the 'work-related training' data items are not comparable over time they should not be used in conjunction with the data in earlier editions of this publication.

the collection of parental information (employment and education) for persons aged 15-24 years;

the collection of data about time spent on formal learning and associated costs;

changes to the collection of employment and income information to align with new ABS standards.

52 Selected summary results from the 2005 SET have been presented in this publication to allow comparisons over time to be made. The statistical significance of data changes between 2005 and 2009 has been investigated and results that are statistically significant are indicated in tables 4, 10, 12 and 16. A detailed listing outlining the comparability of data items between the 2005 and 2009 cycles will be made available on the ABS website to coincide with the release of the confidentialised unit record files (CURFs) to assist users with understanding the comparability of SET data over time.

53 The National Centre for Education and Training Statistics (NCETS) in the ABS can provide further advice on the comparability of the 2009 survey results with those from earlier surveys.

COMPARABILITY WITH OTHER ABS SOURCES

54 Estimates from the SET may differ from the estimates produced from other ABS collections for several reasons. The SET is a sample survey and its results are subject to sampling error. Results may differ from other sample surveys, which are also subject to sampling error. Users should take account of the RSEs on estimates and those of other survey estimates where comparisons are made.

55 Differences in SET estimates, when compared with the estimates of other surveys, may also result from:

differences in scope and/or coverage;

different reference periods reflecting seasonal variations;

non-seasonal events that may have impacted on one period but not another; or

because of underlying trends in the phenomena being measured.

56 Finally, differences can occur as a result of using different collection methodologies. This is often evident in comparisons of similar data items reported from different ABS collections where, after taking account of definition and scope differences and sampling error, residual differences remain. These differences are often the result of the mode of the collections, such as whether data are collected by an interviewer or self-enumerated by the respondent, whether the data are collected from the person themselves or from a proxy respondent, and the level of experience of the interviewers. Differences may also result from the context in which questions are asked, i.e. where in the interview the questions are asked and the nature of preceding questions. The impacts on data of different collection methodologies are difficult to quantify. As a result, every effort is made to minimise such differences.

COMPARISON OF DATA FROM SET WITH OTHER ABS SOURCES, Persons aged 15-64 years

SET

SEW

ALLS

%

%

%

Highest year of school completed

Year 12

51.0

54.0

50.0

Year 11

12.0

11.0

12.0

Year 10 or below(a)

36.0

34.0

39.0

Level of highest non-school qualificaiton

Postgraduate Degree/Graduate Diploma/Graduate Certificate

8.0

7.0

6.0

Bachelor degree

14.0

16.0

15.0

Advanced Diploma/Diploma

10.0

9.0

9.0

Certificate III and IV

17.0

16.0

16.0

Certificate I and II

6.0

5.0

7.0

Total(b)

57.0

55.0

56.0

Main field of highest non-school qualificaiton

Natural and Physical Sciences

2.0

2.0

2.0

Information Technology

2.0

2.0

2.0

Engineering and Related Technologies

9.0

10.0

10.0

Architecture and Building

3.0

4.0

3.0

Agriculture Environmental and Related Studies

1.0

1.0

2.0

Health

5.0

5.0

5.0

Education

4.0

4.0

4.0

Management and Commerce

13.0

13.0

14.0

Society and Culture

7.0

8.0

7.0

Creative Arts

3.0

2.0

3.0

Food Hospitality and Personal Services

3.0

3.0

4.0

Labour force status

Full-time

50.0

53.0

53.0

Part-time

22.0

22.0

23.0

Unemployed

5.0

5.0

4.0

Not in the Labour Force

23.0

21.0

20.0

Country of birth

Born in Australia

72.0

71.0

73.0

Born overseas

28.0

29.0

27.0

(a) Includes persons who never attended school.

(b) Includes 'Certificate n.f.d' and 'Level not determined'.

58 Although both the SET and the SEW are education surveys, there are a number of key differences between them. Conducted on an annual basis, the SEW provides a range of key indicators of educational participation and attainment and data on people's transition between education and work, and involvement in apprenticeships and traineeships. Conversely, the SET is conducted every four years and provides data on the level and outcomes of the individuals education and training. The SET's additional content includes aspects such as income, more extensive education history, and health and disability. The scope of the SEW is broadly the same as the SET however SEW is based on household interviews with any responsible adult whereas the SET interviews each person in the household who is in scope.

SET PRODUCTS AND SERVICES

59 Below is information describing the range of data to be made available from the 2009 Survey of Education and Training, both in published form and on request. Products available on the ABS website <www.abs.gov.au> are indicated accordingly.

Education and Training Experience, Australia, 2009 datacubes

60 An electronic version of the tables contained in this publication is available on the ABS website (cat. no. 6278.0), in spreadsheet format. The spreadsheet presents RSEs relating to estimates and/or proportions for each publication table.

63 Technical information describing the content and use of the basic and expanded SET CURFs will be available in the Technical Manual: Survey of Education and Training, CURF, Australia: Confidentialised Unit Record File (cat. no. 6278.0.55.001). Up-to-date information on the ABS RADL service, including information on pricing, 'Applications & Undertakings', and a training manual outlining obligations and responsibilities when accessing ABS microdata, is available on the ABS website via the following link; Remote Access Data Laboratory (RADL). Those wishing to access the 2009 SET microdata should contact the ABS using MiCRO, the ABS online CURF registration system.

Data available on request

64 Special tabulations of SET data are available on request and for a fee. Subject to confidentiality and sampling variability constraints, tabulations can be produced from the survey incorporating data items, populations and geographic areas selected to meet individual requirements. These can be provided in printed or electronic form. Please contact the National Information and Referral Service on 1300 135 070 or client.services@abs.gov.au for further information about these or related statistics.

ACKNOWLEDGMENT

65 ABS publications draw extensively on information provided freely by individuals, businesses, governments and other organisations. Their continued cooperation is very much appreciated; without it, the wide range of statistics published by the ABS would not be available. Information received by the ABS is treated in strict confidence as required by the Census and Statistics Act 1905 (CSA).

RELATED PUBLICATIONS

66 Listed below is a selection of other ABS publications on related topics which may be of interest. Information about previous and upcoming ABS publications and products can be found on the ABS website <www.abs.gov.au>. The ABS also issues a Release Calendar which shows the expected release dates for the upcoming six months.